In order to improve the low lane departure warning rate due to the poor robustness of the traditional edge operator in lane feature extraction and the weak fitting ability of the traditional Hough transform curve, this paper proposed a lane departure warning method based on the threshold segmentation of the optimized maximum inter-class variance method (OTSU algorithm) and the sliding window method. Firstly, the genetic annealing algorithm was used to optimize and solve the optimal threshold of OTSU algorithm, and the Holistically-nested Edge Detection (HED) model was invoked to obtain the edge features of lane lines, and the area of interest was converted into an aerial view. Then, the sliding window method was utilized to slice the lane lines and the second-order polynomial fitting was carried out for the lane pixels in the window one by one. Finally, the lane departure warning and curve warning were given according to the relative position of the vehicle and the lane line. The test results show that the accuracy of the proposed method is 95.92%, and the detection rate can reach 34 ms/frame.

This paper proposed a path planning method with low computing power requirement and small parking space for path planning of vertical parking space. First, the one-step and multi-step base path planning for vertical parking were designed based on the linear-arc combination considering the requirements of collision constraints and vehicle kinematic constraints in the parking process. Then, the curvature optimization was combined with the clothoid curve to realize the curvature smoothing of the parking path. Finally, the feasibility of the method was verified by simulation. The results show that the method can plan a safe and smooth parking path for different lateral parking spaces and different initial attitude angles.

A curve braking force control strategy was developed for vehicles equipped with Electro Mechanical Brake (EMB) systems. Firstly, the required braking force was obtained according to the driver’s expected deceleration, and then the braking force was initially distributed based on the vertical load estimate, and then the additional yaw moment control module designed based on the Active Disturbance Rejection Control (ADRC) algorithm was utilized to obtain the additional yaw moment required to improve handling stability of the vehicle, and finally the initially assigned braking force was adjusted through the braking force adjustment module. Simulink and CarSim were applied to co-simulate and compare with the proportional distribution scheme, and the results show that the four wheels are not easy to lock in curve braking when the control strategy proposed in this research is used, and the yaw rate and sideslip angle are closer to their ideal values, which effectively improves the safety of cornering braking.

For the situation that the current automatic parking system requires a high number of sensors and computing power, this paper proposed an automatic parking system based on panoramic images and human-machine interaction. Quantitative perception training was performed on the improved Vacant Parking Slot Network (VPS-Net) to realize real-time parking slot detection and parking slot occupancy classification. At the same time, with the help of the driver’s judgment on the surrounding environment, only 4 surround-view fisheye cameras around the car body were used to complete unoccupied parking slot detection and real-time monitoring of the parking environment, and multi-stage path planning and path-following controller were utilized to realize smooth and accurate parking of the vehicle into the parking slot. The verification results show that the system can realize automatic parking under various typical parking slots and lighting conditions.

To address some of the problems in existing distracted driving behavior detection methods, such as low detection accuracy and poor real-time performance, a deep learning-based target detection method was used for driver distracted driving behavior detection. Firstly, a distracted driving behavior dataset was constructed, including images of drivers using mobile phones, drinking water and smoking, and the targets were annotated, secondly a lightweight target detection model NanoDet was selected for training and validation. The results show that the method can accurately and quickly identify driver behaviors including using mobile phones, drinking water and smoking while driving.

To provide the typical hazardous distracted driving scenarios for the development and testing of vehicle active safety systems, this research relied upon an in-depth investigation of 375 distracted driving accidents, determined parameters of the scenarios across three dimensions including road environment, participant’s speed, and motion state, compared and analyzed national statistics with samples from each accident type and extracted key feature parameters. Using the two-step cluster analysis method, this research obtained typical distracted driving scenarios of 11 different accident types associated with distracted driving, these scenarios were further refined to derive 4 core test scenarios by integrating key feature parameters.

In order to improve the intelligent level of evidence collection and responsibility determination of traffic accidents, this article proposed a vehicle information management and accident forensics system based on blockchain and consensus mechanism. Vehicle information was managed in a permissioned blockchain framework, and the communication between the Electronic Control Unit (ECU) of the vehicle and the Road Side Unit (RSU) was used to ensure the legitimacy and integrity of vehicle data. In the proposed traffic accident digital forensics scheme, the data from involved vehicles was automatically managed by the RSU, and a consensus on data reliability was achieved through the practical Byzantine Fault Tolerance (pBFT) protocol. The experimental results show that the proposed blockchain scheme is able to meet the real-time requirements of transportation applications, and the block generation delay and Q-A verification delay in the experimental scenario do not exceed 18.13 ms and 1.55 ms, respectively. The qualitative results show that the proposed framework is able to resist known security attacks, ensure data reliability, and can help law enforcement achieve fair traffic accident liability determination.

In order to study the noise source characteristics of integrated electric drive assembly, this paper proposed a joint algorithm of RVMD-RobustICA-ST combined with coherence analysis method. Firstly, the spatial dimension of the noise was estimated by Rule of Dominant Eigenvalues(RDE) based on Singular Value Decomposition(SVD), and the variational modal decomposition was subjected to targeted conditional constraints, and then Robust Independent Component Analysis(RobustICA) combined with variational modal decomposition to extract signal features. Secondly, S Transform and Fast Fourier Transform were used to identify the time-frequency characteristics of each component signal. Finally, on the basis of analyzing the waveform error of the component signal using the quadratic residual method, a linear system was established with the vibration signal, noise signal, and time-frequency overlapping component signal of the electric drive assembly as variables for coherence analysis. The results show that the meshing vibration noise of the second gear pair of the reducer has the greatest contribution to the noise of the electric drive assembly under steady state conditions, and the noise energy of the time-frequency overlapping component signal is mainly provided by the meshing vibration of the first gear pair of the reducer.

In order to meet the urgent demand of water-gas separation at the anode hydrogen outlet of the vehicle fuel cell stack and in view of the problems of large space occupation and low water-gas separation efficiency, this paper proposed a new box-type dual-baffle water gas separation device design based on the principle of baffle separation. Through CFD and finite element modeling and simulation methods, combined with the actual working conditions of hydrogen recirculation in a 60 kW fuel cell system, the separation efficiency of the device was simulated and analyzed. The influence of key factors such as inlet and outlet diameter, front and rear baffle length, distance from the inner wall, inclination angle, arc radius and angle on the separation efficiency was studied, and the optimal structural parameters of the device was determined which obviously improved the separation efficiency.

In order to verify the performance of vehicle under the functional interaction between Integrated Boosting System (IBS) and Electronic Stability Control (ESC), troubleshoot and locate the faults when IBS and ESC are interacted, this paper proposes a redundant brake electrical system multiple mechatronics Hardware In the Loop (m-HIL) testing platform scheme based on m-HIL technology, which could test function and performance of brake electrical system under functional interaction between IBS and ESC. According to the combined testing method, regenerative braking condition testing under IBS and ESC redundant controllers was accomplished. In addition, the parameter space corresponding to brake boosting failure under regenerative braking condition was abstracted, the typical test cases of braking boost failure under regenerative braking condition between IBS and ESC were formed.